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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Ly Quang Vu
University Information Techonology
Computer Science & IT Engineering

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Implementation of FaceNet and support vector machine in a real-time web-based timekeeping application Ly Quang Vu; Phan Thanh Trieu; Hoang-Sy Nguyen
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i1.pp388-396

Abstract

This paper presents in detail how to build up and implement a real-time web-based face recognition application. The system works so that images of people are recorded and compared with the references on the database. If they match, the information about their presence will be recorded. As for the system architecture, the multi-task cascaded neural network was deployed for face detection. Followingly, for the recognizing tasks, we conducted a study to compare the accuracy level of three different face recognizing methods on three different public datasets by means of both the literature review and our simulation. From the comparison, it can be drawn that the FaceNet algorithm in-used with the support vector machine (SVM) classifier performs the best among others and is the most suitable candidate for the practical deployment. Eventually, the proposed system can deliver a highly satisfactory result, proving its potentials not only for the research but also the commercial purposes.
Co-Authors Hoang-Sy Nguyen Phan Thanh Trieu